Accession Number:

ADA460966

Title:

Regularized Kernel Regression for Image Deblurring

Descriptive Note:

Conference paper

Corporate Author:

CALIFORNIA UNIV SANTA CRUZ ELECTRICAL ENGINEERING DEPT

Report Date:

2006-01-01

Pagination or Media Count:

6.0

Abstract:

The framework of kernel regression, a nonparametric estimation method, has been widely used in different guises for solving a variety of image processing problems including denoising and interpolation. In this paper, we extend the use of kernel regression for deblurring applications. Furthermore, we show that many of the popular image reconstruction techniques are special cases of the proposed framework. Simulation results confirm the effectiveness of our proposed methods.

Subject Categories:

  • Cybernetics
  • Statistics and Probability
  • Photography
  • Optical Detection and Detectors
  • Active and Passive Radar Detection and Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE